AAPL iphone release¶

In [1]:
import yfinance as yf
import pandas as pd
import plotly.express as px
In [2]:
data = yf.download("AAPL", start="2012-01-01" ,end = "2023-05-01", interval="1mo")

[*********************100%***********************]  1 of 1 completed
In [3]:
data['Returns'] = data['Adj Close'].pct_change()
data
Out[3]:
Open High Low Close Adj Close Volume Returns
Date
2012-01-01 14.621429 16.365713 14.607143 16.302856 13.856495 6859854400 NaN
2012-02-01 16.371786 19.557501 16.213572 19.372856 16.465820 11368554400 0.188311
2012-03-01 19.577499 22.194643 18.436428 21.412500 18.199396 15584338000 0.105283
2012-04-01 21.493929 23.000000 19.821428 20.856428 17.726772 15598990400 -0.025969
2012-05-01 20.889286 21.312857 18.649286 20.633215 17.537058 11106345600 -0.010702
... ... ... ... ... ... ... ...
2022-12-01 148.210007 150.919998 125.870003 129.929993 129.552719 1675731200 -0.120816
2023-01-01 130.279999 147.229996 124.169998 144.289993 143.871017 1443652500 0.110521
2023-02-01 143.970001 157.380005 141.320007 147.410004 146.981964 1307198900 0.021623
2023-03-01 146.830002 165.000000 143.899994 164.899994 164.672226 1520266600 0.120357
2023-04-01 164.270004 169.850006 159.779999 169.679993 169.445618 969709700 0.028987

136 rows × 7 columns

In [4]:
# resample the data
monthly = data.Returns.resample("M").sum()
toHeatMap = pd.DataFrame(monthly)
toHeatMap["Month"] = toHeatMap.index.month
toHeatMap["Year"] = toHeatMap.index.year
Show = toHeatMap.groupby(by=['Month', 'Year']).sum().unstack()
Show.columns = Show.columns.droplevel(0)
Show.rename(columns={1: "January", 2: "February", 3: "March", 4: "April", 5: "May", 6: "June",
                     7: "July", 8: "August", 9: "September", 10: "October", 11: "November", 12: "December"},
            inplace=True)
Show
Out[4]:
Year 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023
Month
1 0.000000 -0.144090 -0.107696 0.061424 -0.075242 0.047746 -0.010636 0.055154 0.054010 -0.005502 -0.015712 0.110521
2 0.188311 -0.030934 0.051219 0.096449 -0.006678 0.128883 0.063848 0.040315 -0.116798 -0.081085 -0.055269 0.021623
3 0.105283 0.008699 0.026058 -0.027549 0.133327 0.053237 -0.054210 0.101731 -0.067554 0.008845 0.058821 0.120357
4 -0.025969 0.000271 0.099396 0.005787 -0.139921 -0.000070 -0.015020 0.056436 0.155374 0.076218 -0.097131 0.028987
5 -0.010702 0.015696 0.072718 0.040991 0.065287 0.063418 0.130764 -0.127573 0.082165 -0.052107 -0.055883 NaN
6 0.010853 -0.112457 0.033401 -0.033206 -0.036831 -0.053323 -0.005598 0.134873 0.150492 0.100976 -0.080080 NaN
7 0.045822 0.141225 0.028731 -0.032927 0.090063 0.032704 0.027983 0.076394 0.165132 0.064982 0.188634 NaN
8 0.089200 0.076658 0.072176 -0.070404 0.018136 0.102669 0.196227 -0.020184 0.214380 0.040930 -0.032552 NaN
9 0.007102 -0.015029 -0.012184 -0.017389 0.071276 -0.056553 -0.004825 0.077038 -0.100908 -0.066640 -0.119756 NaN
10 -0.107600 0.096382 0.071960 0.083409 0.004334 0.096808 -0.030478 0.110684 -0.060012 0.058657 0.109551 NaN
11 -0.016865 0.063842 0.101204 -0.010042 -0.026598 0.016623 -0.184045 0.074329 0.093606 0.103471 -0.034629 NaN
12 -0.086590 0.014792 -0.067866 -0.106419 0.053335 -0.011706 -0.113616 0.102083 0.116497 0.075797 -0.120816 NaN
In [5]:
# plot the data
fig = px.line(Show)
fig.update_layout(xaxis_title="Month", yaxis_title="Returns",height=700,width=1000)
fig.show()

There's a cyclic trend between the 9th month and the 10th month (iphone release: september/october)

Years not correlated:

  • 2012 (release:iphone 5)
  • 2016 (release:iphone 7/7plus)
  • 2018 (release: iphone xr/xs/xs max)
In [6]:
df = pd.read_html('https://en.wikipedia.org/wiki/IPhone')[3]
df
Out[6]:
model release(d) discontinued support
model with OS date discontinued ended final OS[a] lifespan[b]
model with OS date discontinued ended final OS[a] max[c] min[d]
0 iPhone iPhone OS 1.0 June 29, 2007 June 9, 2008 June 20, 2010 iPhone OS 3.1.3 2 years, 11 months 2 years
1 iPhone 3G iPhone OS 2.0 July 11, 2008 August 9, 2010 March 3, 2011 iOS 4.2.1 2 years, 7 months 6 months
2 iPhone 3GS iPhone OS 3.0 June 19, 2009 September 12, 2012 September 18, 2013 (late, single update: Febru... iOS 6.1.3 (6.1.6) 4 years, 2 months 1 year
3 iPhone 4 iOS 4.0 June 24, 2010 September 10, 2013 September 17, 2014 iOS 7.1.2 4 years, 2 months 1 year
4 iPhone 4S iOS 5.0 October 14, 2011 September 9, 2014 September 12, 2016 (late, single update: July ... iOS 9.3.5 (9.3.6) 4 years, 10 months 2 years
5 iPhone 5 iOS 6.0 September 21, 2012 September 10, 2013 September 18, 2017 (late, single update: July ... iOS 10.3.3 (10.3.4) 4 years, 11 months 4 years
6 iPhone 5C iOS 7.0 September 20, 2013 September 9, 2015 September 18, 2017 iOS 10.3.3 3 years, 11 months 2 years
7 iPhone 5S iOS 7.0 September 20, 2013 March 21, 2016 September 18, 2019 (last security update: Janu... iOS 12.4.1 (12.5.7) 5 years, 11 months 3 years, 5 months
8 iPhone 6 / 6 Plus iOS 8.0 September 19, 2014 September 7, 2016 September 18, 2019 (last security update: Janu... iOS 12.4.1 (12.5.7) 4 years, 11 months 3 years
9 iPhone 6S / 6S Plus iOS 9.0 September 25, 2015 September 12, 2018 August 17, 2022 still supported (latest securi... iOS 15.6.1 (15.7.6) 7 years, 7 months 4 years, 8 months
10 iPhone SE (1st) iOS 9.3 March 31, 2016 September 12, 2018 August 17, 2022 still supported (latest securi... iOS 15.6.1 (15.7.6) 7 years, 1 month 4 years, 8 months
11 iPhone 7 / 7 Plus iOS 10.0 September 16, 2016 September 10, 2019 August 17, 2022 still supported (latest securi... iOS 15.6.1 (15.7.6) 6 years, 8 months 3 years, 8 months
12 iPhone 8 / 8 Plus iOS 11.0 September 22, 2017 April 15, 2020 current latest iOS 5 years, 9 months 3 years, 2 months
13 iPhone X iOS 11.0.1 November 3, 2017 September 12, 2018 current latest iOS 5 years, 7 months 4 years, 9 months
14 iPhone XR iOS 12.0 October 26, 2018 September 14, 2021 current latest iOS 4 years, 8 months 1 year, 9 months
15 iPhone XS / XS Max iOS 12.0 September 21, 2018 September 10, 2019 current latest iOS 4 years, 9 months 3 years, 9 months
16 iPhone 11 iOS 13.0 September 20, 2019 September 7, 2022 current latest iOS 3 years, 9 months 9 months
17 iPhone 11 Pro / 11 Pro Max iOS 13.0 September 20, 2019 October 13, 2020 current latest iOS 3 years, 9 months 2 years, 8 months
18 iPhone SE (2nd) iOS 13.4 April 24, 2020 March 8, 2022 current latest iOS 3 years, 2 months 1 year, 3 months
19 iPhone 12 iOS 14.1 October 23, 2020 NaN current latest iOS 2 years, 8 months NaN
20 iPhone 12 Mini iOS 14.2 November 13, 2020 September 7, 2022 current latest iOS 2 years, 7 months 9 months
21 iPhone 12 Pro / 12 Pro Max iOS 14.1 (12 Pro) iOS 14.2 (12 Pro Max) October 23, 2020 November 13, 2020 September 14, 2021 current latest iOS 2 years, 8 months (12 Pro) 2 years, 7 months (... 1 year, 9 months
22 iPhone 13 / 13 Mini iOS 15.0 September 24, 2021 NaN current latest iOS 1 year, 9 months NaN
23 iPhone 13 Pro / 13 Pro Max iOS 15.0 September 24, 2021 September 7, 2022 current latest iOS 1 year, 9 months 9 months
24 iPhone SE (3rd) iOS 15.4 March 18, 2022 NaN current latest iOS 1 year, 3 months NaN
25 iPhone 14 / 14 Plus iOS 16.0 September 16, 2022 October 7, 2022 NaN current latest iOS 9 months NaN
26 iPhone 14 Pro / 14 Pro Max iOS 16.0 September 16, 2022 NaN current latest iOS 9 months NaN
27 Legend: Discontinued and unsupported Discont... Legend: Discontinued and unsupported Discont... Legend: Discontinued and unsupported Discont... Legend: Discontinued and unsupported Discont... Legend: Discontinued and unsupported Discont... Legend: Discontinued and unsupported Discont... Legend: Discontinued and unsupported Discont... Legend: Discontinued and unsupported Discont...
28 Legend: Discontinued and unsupported Discontinued, bug fixes only Discontinued, still supported Current or still sold NaN NaN NaN
29 Remarks: .mw-parser-output .reflist{font-size:... Remarks: .mw-parser-output .reflist{font-size:... Remarks: .mw-parser-output .reflist{font-size:... Remarks: .mw-parser-output .reflist{font-size:... Remarks: .mw-parser-output .reflist{font-size:... Remarks: .mw-parser-output .reflist{font-size:... Remarks: .mw-parser-output .reflist{font-size:... Remarks: .mw-parser-output .reflist{font-size:...
30 Remarks: .mw-parser-output .reflist{font-size:90%;margi... NaN NaN NaN NaN NaN NaN
In [7]:
data['Month']= data.index.month
signal_series = data[(data['Month'] == 10)]
signal_series
Out[7]:
Open High Low Close Adj Close Volume Returns Month
Date
2012-10-01 23.969999 24.169643 20.989286 21.261429 18.148588 12142830000 -0.107600 10
2013-10-01 17.087500 19.258928 17.081429 18.667856 16.314390 7837732000 0.096382 10
2014-10-01 25.147499 27.010000 23.795000 27.000000 24.128706 5441120800 0.071960 10
2015-10-01 27.267500 30.305000 26.827499 29.875000 27.154360 4450048400 0.083409 10
2016-10-01 28.177500 29.672501 28.070000 28.385000 26.351681 2747657200 0.004334 10
2017-10-01 38.564999 42.412498 38.115002 42.259998 39.924809 2017165200 0.096808 10
2018-10-01 56.987499 58.367500 51.522499 54.715000 52.473160 3158994000 -0.030478 10
2019-10-01 56.267502 62.437500 53.782501 62.189999 60.567390 2433210800 0.110684 10
2020-10-01 117.639999 125.389999 107.720001 108.860001 107.071648 2894666500 -0.060012 10
2021-10-01 141.899994 153.169998 138.270004 149.800003 148.286743 1565079200 0.058657 10
2022-10-01 138.210007 157.500000 134.369995 153.339996 152.641541 1868139700 0.109551 10
In [8]:
money = 10000
returns1 = signal_series['Returns'] * money
equity = returns1.cumsum() + money
In [9]:
equity
Out[9]:
Date
2012-10-01     8924.000474
2013-10-01     9887.817697
2014-10-01    10607.416076
2015-10-01    11441.506094
2016-10-01    11484.849314
2017-10-01    12452.925822
2018-10-01    12148.149349
2019-10-01    13254.994205
2020-10-01    12654.874768
2021-10-01    13241.448461
2022-10-01    14336.962791
Name: Returns, dtype: float64
In [10]:
# plot the Equity
fig = px.line(equity)
fig.update_layout(xaxis_title="Month", yaxis_title="Returns",height=600,width=1000)
fig.show()